Mapping network topology for latency sensitive applications in a mobile network

ABSTRACT

Aspects of the subject disclosure may include, for example, a device in which a processing system enables mobile devices on a communication network to perform latency tests to obtain first latency test data, determines an edge latency for each mobile device resulting in edge latencies, identifies a group of mobile device clusters according to the edge latencies, and identifies network edge server locations according to the group of mobile device clusters. The processing system also receives second latency test data from each of the network edge servers, and determines a data center latency for each of the network edge servers, resulting in a plurality of data center latencies. The processing system also identifies a data center location according to the data center latencies, and determines a network topology for the communication network; the network topology includes the data center location and the edge server locations. Other embodiments are disclosed.

FIELD OF THE DISCLOSURE

The subject disclosure relates to a network for wireless communicationbetween mobile devices, and more particularly to a method and system formapping a network topology for latency-sensitive applications on thatnetwork.

BACKGROUND

Delay-sensitive applications on mobile networks are becoming morepopular. The end-to-end communication delay (latency) experienced by auser communication device (user equipment or UE) can vary with thelocation of the device.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and wherein:

FIG. 1 is a block diagram illustrating an exemplary, non-limitingembodiment of a communications network in accordance with variousaspects described herein.

FIG. 2A is a block diagram illustrating an example, non-limitingembodiment of a system functioning within the communication network ofFIG. 1 and including a network edge, in accordance with various aspectsdescribed herein.

FIG. 2B illustrates a scatter plot of locations of latency testsperformed with UEs, in accordance with embodiments of the disclosure.

FIG. 2C illustrates a density plot of the locations in FIG. 2B, inaccordance with embodiments of the disclosure.

FIG. 2D schematically illustrates a procedure for estimating a networkdata center location, in accordance with embodiments of the disclosure.

FIG. 2E schematically illustrates end-to-end network topology associatedwith a UE, in accordance with embodiments of the disclosure.

FIG. 2F depicts an illustrative embodiment of a method in accordancewith various aspects described herein.

FIG. 3 is a block diagram illustrating an example, non-limitingembodiment of a virtualized communication network in accordance withvarious aspects described herein.

FIG. 4 is a block diagram of an example, non-limiting embodiment of acomputing environment in accordance with various aspects describedherein.

FIG. 5 is a block diagram of an example, non-limiting embodiment of amobile network platform in accordance with various aspects describedherein.

FIG. 6 is a block diagram of an example, non-limiting embodiment of acommunication device in accordance with various aspects describedherein.

DETAILED DESCRIPTION

The subject disclosure describes, among other things, illustrativeembodiments for mapping a network topology for a network includingnetwork edge servers and data center servers, based on latency dataobtained from mobile devices communicating on the network. Otherembodiments are described in the subject disclosure.

One or more aspects of the subject disclosure include a devicecomprising a processing system including a processor and a memory thatstores executable instructions that, when executed by the processingsystem, facilitate performance of operations. The operations includereceiving first latency test data from each of a plurality of mobiledevices operating on a communication network, and determining an edgelatency for each of the plurality of mobile devices according to thefirst latency test data, resulting in a plurality of edge latencies. Theoperations also include identifying a group of mobile device clustersaccording to the plurality of edge latencies, and identifying edgeserver locations for a plurality of network edge servers according tothe group of mobile device clusters. The operations further includereceiving second latency test data from each of the plurality of networkedge servers, and determining a data center latency for each of theplurality of network edge servers according to the second latency testdata, resulting in a plurality of data center latencies. The operationsalso include identifying a data center location for a data centeraccording to the plurality of data center latencies, and determining anetwork topology for the communication network; the network topologyincludes the data center location and the edge server locations.

One or more aspects of the subject disclosure include a machine-readablemedium comprising executable instructions that, when executed by aprocessing system including a processor, facilitate performance ofoperations. The operations include enabling each of a plurality ofmobile devices operating on a communication network to perform a latencytest to obtain first latency test data, and determining an edge latencyfor each of the plurality of mobile devices according to the firstlatency test data, resulting in a plurality of edge latencies. Theoperations also include identifying a group of mobile device clustersaccording to the plurality of edge latencies, and identifying edgeserver locations for a plurality of network edge servers according tothe group of mobile device clusters. The operations further includereceiving second latency test data from each of the plurality of networkedge servers, and determining a data center latency for each of theplurality of network edge servers according to the second latency testdata, resulting in a plurality of data center latencies. The operationsalso include identifying a data center location for a data centeraccording to the plurality of data center latencies, and determining anetwork topology for the communication network; the network topologyincludes the data center location and the edge server locations.

One or more aspects of the subject disclosure include a method thatincludes receiving, by a processing system including a processor, firstlatency test data from each of a plurality of mobile devices operatingon a communication network, and determining an edge latency for each ofthe plurality of mobile devices according to the first latency testdata, resulting in a plurality of edge latencies. The method alsoincludes identifying a group of mobile device clusters according to theplurality of edge latencies by performing a machine learning clusteringtechnique, and identifying edge server locations for a plurality ofnetwork edge servers according to the group of mobile device clusters.The method further includes receiving second latency test data from eachof the plurality of network edge servers, and determining a data centerlatency for each of the plurality of network edge servers according tothe second latency test data, resulting in a plurality of data centerlatencies. The method also includes identifying a data center locationfor a data center according to the plurality of data center latencies,and determining a network topology for the communication network, thenetwork topology including the data center location and the edge serverlocations.

Referring now to FIG. 1, a block diagram is shown illustrating anexample, non-limiting embodiment of a communications network 100 inaccordance with various aspects described herein. For example,communications network 100 can facilitate in whole or in part receivingfirst latency test data from each of a plurality of mobile devicesoperating on the communication network, and receiving second latencytest data from each of a plurality of network edge servers. Inparticular, a communications network 125 is presented for providingbroadband access 110 to a plurality of data terminals 114 via accessterminal 112, wireless access 120 to a plurality of mobile devices 124and vehicle 126 via base station or access point 122, voice access 130to a plurality of telephony devices 134, via switching device 132 and/ormedia access 140 to a plurality of audio/video display devices 144 viamedia terminal 142. In addition, communication network 125 is coupled toone or more content sources 175 of audio, video, graphics, text and/orother media. While broadband access 110, wireless access 120, voiceaccess 130 and media access 140 are shown separately, one or more ofthese forms of access can be combined to provide multiple accessservices to a single client device (e.g., mobile devices 124 can receivemedia content via media terminal 142, data terminal 114 can be providedvoice access via switching device 132, and so on).

The communications network 125 includes a plurality of network elements(NE) 150, 152, 154, 156, etc. for facilitating the broadband access 110,wireless access 120, voice access 130, media access 140 and/or thedistribution of content from content sources 175. The communicationsnetwork 125 can include a circuit switched or packet switched network, avoice over Internet protocol (VoIP) network, Internet protocol (IP)network, a cable network, a passive or active optical network, a 4G, 5G,or higher generation wireless access network, WIMAX network,UltraWideband network, personal area network or other wireless accessnetwork, a broadcast satellite network and/or other communicationsnetwork.

In various embodiments, the access terminal 112 can include a digitalsubscriber line access multiplexer (DSLAM), cable modem terminationsystem (CMTS), optical line terminal (OLT) and/or other access terminal.The data terminals 114 can include personal computers, laptop computers,netbook computers, tablets or other computing devices along with digitalsubscriber line (DSL) modems, data over coax service interfacespecification (DOCSIS) modems or other cable modems, a wireless modemsuch as a 4G, 5G, or higher generation modem, an optical modem and/orother access devices.

In various embodiments, the base station or access point 122 can includea 4G, 5G, or higher generation base station, an access point thatoperates via an 802.11 standard such as 802.11n, 802.11ac or otherwireless access terminal. The mobile devices 124 can include mobilephones, e-readers, tablets, phablets, wireless modems, and/or othermobile computing devices.

In various embodiments, the switching device 132 can include a privatebranch exchange or central office switch, a media services gateway, VoIPgateway or other gateway device and/or other switching device. Thetelephony devices 134 can include traditional telephones (with orwithout a terminal adapter), VoIP telephones and/or other telephonydevices.

In various embodiments, the media terminal 142 can include a cablehead-end or other TV head-end, a satellite receiver, gateway or othermedia terminal 142. The display devices 144 can include televisions withor without a set top box, personal computers and/or other displaydevices.

In various embodiments, the content sources 175 include broadcasttelevision and radio sources, video on demand platforms and streamingvideo and audio services platforms, one or more content data networks,data servers, web servers and other content servers, and/or othersources of media.

In various embodiments, the communications network 125 can includewired, optical and/or wireless links and the network elements 150, 152,154, 156, etc. can include service switching points, signal transferpoints, service control points, network gateways, media distributionhubs, servers, firewalls, routers, edge devices, switches and othernetwork nodes for routing and controlling communications traffic overwired, optical and wireless links as part of the Internet and otherpublic networks as well as one or more private networks, for managingsubscriber access, for billing and network management and for supportingother network functions.

FIG. 2A is a block diagram illustrating an example, non-limitingembodiment of a system 201 functioning within the communication networkof FIG. 1, in accordance with various aspects of the disclosure. Asshown schematically in FIG. 2A, numerous mobile devices have wirelessconnections with base stations that communicate with a server (e.g.devices 212, 214 having wireless connections 213, 215 with base stations217, 219, which in turn communicate with a network edge server 211). Forimproved performance, it is desirable that delay-sensitive applicationsexecuting on the mobile devices, such as online video gaming, videochatting, virtual reality (VR), etc., be aware of the end-to-end latencyof the network communication path. In general, the end-to-end latencyfor a given mobile device (also referred to herein as user equipment orUE) is dynamic; that is, the latency can change with time and with thelocation of the mobile device.

In various embodiments, latency data is crowdsourced from a large numberof UEs in a mobile network, and analyzed to map the topology of thenetwork. Based on the network topology map, latency can then beestimated for other UEs sharing the same network topology.

In an embodiment, a processing system enables a large number of UEs toperform a very large number (>100,000) of tests (Ping and/or Traceroutetests, as is understood in the art) from different locations. In otherembodiments, different numbers of tests can be performed. For each test,the system obtains the location of the UE (e.g. UE 212, as shown in FIG.2A) and the latency from the UE to the edge server 211. In thisembodiment, a portion of the test results showing the lowest latency(e.g. the lowest 10% of all latencies reported) is selected as anestimator of a network edge location in the network topology. Ingeneral, the locations for the lowest-latency tests are close to thenetwork edge. In FIG. 2A, for example, UE locations corresponding totests meeting the lowest-10% criterion are within boundary 210. Suchlocations are treated as a cluster, as detailed below.

In an embodiment, each network edge is associated with a specific IPaddress (or an IP prefix). In this embodiment, the IP address/prefix isassociated with the router closest to the packet gateway (PGW) of thenetwork edge; the IP address/prefix may then be treated as a valididentifier of the network edge.

FIG. 2B illustrates a scatter plot 202 of locations of latency testsperformed with UEs, in accordance with embodiments of the disclosure.Each dot (e.g. 220) represents the location of a latency test performedby the UE. The reported locations may be expressed using geographicallatitude 221 and longitude 222. In this embodiment, the plottedlocations correspond to tests meeting a low-latency criterion; a cluster225 of such locations is estimated to be an edge server location in thenetwork topology.

FIG. 2C illustrates a density plot 203 of the location data from FIG.2B. In this embodiment, the density of low-latency tests is also plottedas a function 233 of longitude at a fixed latitude 231, and a function234 of latitude at a fixed longitude 232. The location 235 with thehighest density (at the intersection of axes 231, 232 corresponding tothe maximum values of functions 234, 233) is estimated as the locationof the network edge server in the network topology.

In an embodiment, machine learning (ML) techniques are used to reducethe estimation error for network edge server locations. Specifically, amachine learning clustering method can be used to aggregate IP locationsinto clusters; a cluster location is calculated by the lowest-latencytests associated with the IP addresses in that cluster. In thisembodiment, a cluster location is considered to be a network edgelocation.

FIG. 2D schematically illustrates a procedure 204 for estimating anetwork data center location, in accordance with embodiments of thedisclosure. The location of data center 240 in the network topology canbe determined once the locations of at least three network edge servers241-243 are known.

In an embodiment, a large number of UEs 245 are enabled to performPing/Traceroute tests (e.g. test 244 via base station 246) directed toan IP address in data center 240. The UE/edge latencies and network edgelocations can be determined from the procedure described above withreference to FIG. 2C. For each network edge server 241-243, thelatencies associated with the various UEs can be aggregated to obtain anaverage latency 271-273 with respect to the data center 240. Thelocation of the data center in the network topology can then beestimated from the latencies 271-273.

FIG. 2E schematically illustrates an end-to-end network topology 205associated with a UE, in accordance with embodiments of the disclosure.In general, as shown in FIG. 2E, the end-to-end network topology isdetermined from UE locations, network edge locations and data centerlocations.

Furthermore, end-to-end latency typically includes three components: (1)latency introduced by radio access network (RAN) connections between UEand a base station; (2) latency between a base station and a networkedge server, often referred to as core network latency; and (3) latencybetween a network edge server and an internet data center, oftenreferred to as internet latency.

In an embodiment, the distance 281 from a given UE location 251 tonetwork edge server 252 is estimated from results of UE/edge latencytests, and the distance 282 from edge server 252 to data center 250 isestimated from results of edge/data center latency tests, as describedabove. These respective distances can then be converted (using a knownsignal speed, e.g. the speed of light in the atmosphere, in a fiber,and/or in a router) to obtain the core network latency and internetlatency associated with a given location.

It will be appreciated that, once the network topology is mapped, it isnot necessary to estimate the core network latency or internet latencyfor an individual UE at a given location. The overall latency (whichincludes the RAN latency of the UE) can then be estimated moreaccurately and consistently, compared with a latency measurement for theindividual UE.

FIG. 2F is a flowchart 206 depicting an illustrative embodiment of amethod for mapping a network topology, in accordance with variousaspects described herein. In step 2602, a processing system incommunication with a network enables user devices (UEs) to performlatency tests on the network; in various embodiments, these may be Pingor Traceroute tests. The system receives test results from the variousUEs (step 2604); in an embodiment, each test result includes the testlocation in a data packet received by the system. The system thendetermines the UE/edge latencies based on the test results (step 2606);in an embodiment, the test locations and UE/edge latencies may beplotted as shown in FIG. 2B.

The system then identifies clusters of low-latency tests (e.g. testsrepresenting the lowest 10% of all latencies) in step 2608; in anembodiment, this is done by applying a machine-learning clusteringtechnique to aggregate IP address locations into clusters. The clusterlocations (such as shown in FIG. 2B) in this embodiment also correspondto high-density locations on a contour plot of latency tests (such asshown in FIG. 2C). The location of edge network servers in the networktopology is estimated from the cluster locations (step 2610).

The system then enables Ping or Traceroute tests from network edgeservers to a data center (step 2612). The system receives test resultsfrom the various network edge servers (step 2614) and determines thelatencies from the network edge servers to the data center (step 2616).The system can then convert the edge server/data center latencies todistances, and thus derive the network topology including data centerlocations and network edge server locations (step 2618).

In an embodiment, the end-to-end latency for an individual UE at a givenlocation can be estimated in a procedure 2620 using the networktopology. The system obtains the location of the UE (step 2621),estimates the core network latency from the topology based on the UElocation (step 2622), and estimates the internet latency from thetopology based on the UE location (step 2623). The core network latencyand internet latency estimates can then be combined with the radioaccess network (RAN) latency estimated for the UE (step 2624), to obtainan estimate of the end-to-end latency for the UE at that location.

While for purposes of simplicity of explanation, the respectiveprocesses are shown and described as a series of blocks in FIG. 2F, itis to be understood and appreciated that the claimed subject matter isnot limited by the order of the blocks, as some blocks may occur indifferent orders and/or concurrently with other blocks from what isdepicted and described herein. Moreover, not all illustrated blocks maybe required to implement the methods described herein.

Referring now to FIG. 3, a block diagram 300 is shown illustrating anexample, non-limiting embodiment of a virtualized communication networkin accordance with various aspects described herein. In particular avirtualized communication network is presented that can be used toimplement some or all of the subsystems and functions of communicationnetwork 100, the subsystems and functions of system 201, and method 206presented in FIGS. 1, 2A, 2F, and 3. For example, virtualizedcommunication network 300 can facilitate in whole or in part determiningan edge latency for each of a plurality of mobile devices according tofirst latency test data, resulting in a plurality of edge latencies, anddetermining a data center latency for each of a plurality of networkedge servers according to second latency test data, resulting in aplurality of data center latencies.

In particular, a cloud networking architecture is shown that leveragescloud technologies and supports rapid innovation and scalability via atransport layer 350, a virtualized network function cloud 325 and/or oneor more cloud computing environments 375. In various embodiments, thiscloud networking architecture is an open architecture that leveragesapplication programming interfaces (APIs); reduces complexity fromservices and operations; supports more nimble business models; andrapidly and seamlessly scales to meet evolving customer requirementsincluding traffic growth, diversity of traffic types, and diversity ofperformance and reliability expectations.

In contrast to traditional network elements—which are typicallyintegrated to perform a single function, the virtualized communicationnetwork employs virtual network elements (VNEs) 330, 332, 334, etc. thatperform some or all of the functions of network elements 150, 152, 154,156, etc. For example, the network architecture can provide a substrateof networking capability, often called Network Function VirtualizationInfrastructure (NFVI) or simply infrastructure that is capable of beingdirected with software and Software Defined Networking (SDN) protocolsto perform a broad variety of network functions and services. Thisinfrastructure can include several types of substrates. The most typicaltype of substrate being servers that support Network FunctionVirtualization (NFV), followed by packet forwarding capabilities basedon generic computing resources, with specialized network technologiesbrought to bear when general purpose processors or general purposeintegrated circuit devices offered by merchants (referred to herein asmerchant silicon) are not appropriate. In this case, communicationservices can be implemented as cloud-centric workloads.

As an example, a traditional network element 150 (shown in FIG. 1), suchas an edge router can be implemented via a VNE 330 composed of NFVsoftware modules, merchant silicon, and associated controllers. Thesoftware can be written so that increasing workload consumes incrementalresources from a common resource pool, and moreover so that it'selastic: so the resources are only consumed when needed. In a similarfashion, other network elements such as other routers, switches, edgecaches, and middle-boxes are instantiated from the common resource pool.Such sharing of infrastructure across a broad set of uses makes planningand growing infrastructure easier to manage.

In an embodiment, the transport layer 350 includes fiber, cable, wiredand/or wireless transport elements, network elements and interfaces toprovide broadband access 110, wireless access 120, voice access 130,media access 140 and/or access to content sources 175 for distributionof content to any or all of the access technologies. In particular, insome cases a network element needs to be positioned at a specific place,and this allows for less sharing of common infrastructure. Other times,the network elements have specific physical layer adapters that cannotbe abstracted or virtualized, and might require special DSP code andanalog front-ends (AFEs) that do not lend themselves to implementationas VNEs 330, 332 or 334. These network elements can be included intransport layer 350.

The virtualized network function cloud 325 interfaces with the transportlayer 350 to provide the VNEs 330, 332, 334, etc. to provide specificNFVs. In particular, the virtualized network function cloud 325leverages cloud operations, applications, and architectures to supportnetworking workloads. The virtualized network elements 330, 332 and 334can employ network function software that provides either a one-for-onemapping of traditional network element function or alternately somecombination of network functions designed for cloud computing. Forexample, VNEs 330, 332 and 334 can include route reflectors, domain namesystem (DNS) servers, and dynamic host configuration protocol (DHCP)servers, system architecture evolution (SAE) and/or mobility managemententity (MME) gateways, broadband network gateways, IP edge routers forIP-VPN, Ethernet and other services, load balancers, distributers andother network elements. Because these elements don't typically need toforward large amounts of traffic, their workload can be distributedacross a number of servers—each of which adds a portion of thecapability, and overall which creates an elastic function with higheravailability than its former monolithic version. These virtual networkelements 330, 332, 334, etc. can be instantiated and managed using anorchestration approach similar to those used in cloud compute services.

The cloud computing environments 375 can interface with the virtualizednetwork function cloud 325 via APIs that expose functional capabilitiesof the VNEs 330, 332, 334, etc. to provide the flexible and expandedcapabilities to the virtualized network function cloud 325. Inparticular, network workloads may have applications distributed acrossthe virtualized network function cloud 325 and cloud computingenvironment 375 and in the commercial cloud, or might simply orchestrateworkloads supported entirely in NFV infrastructure from these thirdparty locations.

Turning now to FIG. 4, there is illustrated a block diagram of acomputing environment in accordance with various aspects describedherein. In order to provide additional context for various embodimentsof the embodiments described herein, FIG. 4 and the following discussionare intended to provide a brief, general description of a suitablecomputing environment 400 in which the various embodiments of thesubject disclosure can be implemented. In particular, computingenvironment 400 can be used in the implementation of network elements150, 152, 154, 156, access terminal 112, base station or access point122, switching device 132, media terminal 142, and/or VNEs 330, 332,334, etc. Each of these devices can be implemented viacomputer-executable instructions that can run on one or more computers,and/or in combination with other program modules and/or as a combinationof hardware and software. For example, computing environment 400 canfacilitate in whole or in part identifying a group of mobile deviceclusters according to a plurality of edge latencies by performing amachine learning clustering technique, identifying edge server locationsfor a plurality of network edge servers according to the group of mobiledevice clusters, identifying a data center location for a data centeraccording to the plurality of data center latencies, and determining anetwork topology for the communication network.

Generally, program modules comprise routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will appreciatethat the methods can be practiced with other computer systemconfigurations, comprising single-processor or multiprocessor computersystems, minicomputers, mainframe computers, as well as personalcomputers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices.

As used herein, a processing circuit includes one or more processors aswell as other application specific circuits such as an applicationspecific integrated circuit, digital logic circuit, state machine,programmable gate array or other circuit that processes input signals ordata and that produces output signals or data in response thereto. Itshould be noted that while any functions and features described hereinin association with the operation of a processor could likewise beperformed by a processing circuit.

The illustrated embodiments of the embodiments herein can be alsopracticed in distributed computing environments where certain tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules can be located in both local and remote memory storage devices.

Computing devices typically comprise a variety of media, which cancomprise computer-readable storage media and/or communications media,which two terms are used herein differently from one another as follows.Computer-readable storage media can be any available storage media thatcan be accessed by the computer and comprises both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structured dataor unstructured data.

Computer-readable storage media can comprise, but are not limited to,random access memory (RAM), read only memory (ROM), electricallyerasable programmable read only memory (EEPROM), flash memory or othermemory technology, compact disk read only memory (CD-ROM), digitalversatile disk (DVD) or other optical disk storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devicesor other tangible and/or non-transitory media which can be used to storedesired information. In this regard, the terms “tangible” or“non-transitory” herein as applied to storage, memory orcomputer-readable media, are to be understood to exclude onlypropagating transitory signals per se as modifiers and do not relinquishrights to all standard storage, memory or computer-readable media thatare not only propagating transitory signals per se.

Computer-readable storage media can be accessed by one or more local orremote computing devices, e.g., via access requests, queries or otherdata retrieval protocols, for a variety of operations with respect tothe information stored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and comprises any informationdelivery or transport media. The term “modulated data signal” or signalsrefers to a signal that has one or more of its characteristics set orchanged in such a manner as to encode information in one or moresignals. By way of example, and not limitation, communication mediacomprise wired media, such as a wired network or direct-wiredconnection, and wireless media such as acoustic, RF, infrared and otherwireless media.

With reference again to FIG. 4, the example environment can comprise acomputer 402, the computer 402 comprising a processing unit 404, asystem memory 406 and a system bus 408. The system bus 408 couplessystem components including, but not limited to, the system memory 406to the processing unit 404. The processing unit 404 can be any ofvarious commercially available processors. Dual microprocessors andother multiprocessor architectures can also be employed as theprocessing unit 404.

The system bus 408 can be any of several types of bus structure that canfurther interconnect to a memory bus (with or without a memorycontroller), a peripheral bus, and a local bus using any of a variety ofcommercially available bus architectures. The system memory 406comprises ROM 410 and RAM 412. A basic input/output system (BIOS) can bestored in a non-volatile memory such as ROM, erasable programmable readonly memory (EPROM), EEPROM, which BIOS contains the basic routines thathelp to transfer information between elements within the computer 402,such as during startup. The RAM 412 can also comprise a high-speed RAMsuch as static RAM for caching data.

The computer 402 further comprises an internal hard disk drive (HDD) 414(e.g., EIDE, SATA), which internal HDD 414 can also be configured forexternal use in a suitable chassis (not shown), a magnetic floppy diskdrive (FDD) 416, (e.g., to read from or write to a removable diskette418) and an optical disk drive 420, (e.g., reading a CD-ROM disk 422 or,to read from or write to other high capacity optical media such as theDVD). The HDD 414, magnetic FDD 416 and optical disk drive 420 can beconnected to the system bus 408 by a hard disk drive interface 424, amagnetic disk drive interface 426 and an optical drive interface 428,respectively. The hard disk drive interface 424 for external driveimplementations comprises at least one or both of Universal Serial Bus(USB) and Institute of Electrical and Electronics Engineers (IEEE) 1394interface technologies. Other external drive connection technologies arewithin contemplation of the embodiments described herein.

The drives and their associated computer-readable storage media providenonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For the computer 402, the drives and storagemedia accommodate the storage of any data in a suitable digital format.Although the description of computer-readable storage media above refersto a hard disk drive (HDD), a removable magnetic diskette, and aremovable optical media such as a CD or DVD, it should be appreciated bythose skilled in the art that other types of storage media which arereadable by a computer, such as zip drives, magnetic cassettes, flashmemory cards, cartridges, and the like, can also be used in the exampleoperating environment, and further, that any such storage media cancontain computer-executable instructions for performing the methodsdescribed herein.

A number of program modules can be stored in the drives and RAM 412,comprising an operating system 430, one or more application programs432, other program modules 434 and program data 436. All or portions ofthe operating system, applications, modules, and/or data can also becached in the RAM 412. The systems and methods described herein can beimplemented utilizing various commercially available operating systemsor combinations of operating systems.

A user can enter commands and information into the computer 402 throughone or more wired/wireless input devices, e.g., a keyboard 438 and apointing device, such as a mouse 440. Other input devices (not shown)can comprise a microphone, an infrared (IR) remote control, a joystick,a game pad, a stylus pen, touch screen or the like. These and otherinput devices are often connected to the processing unit 404 through aninput device interface 442 that can be coupled to the system bus 408,but can be connected by other interfaces, such as a parallel port, anIEEE 1394 serial port, a game port, a universal serial bus (USB) port,an IR interface, etc.

A monitor 444 or other type of display device can be also connected tothe system bus 408 via an interface, such as a video adapter 446. Itwill also be appreciated that in alternative embodiments, a monitor 444can also be any display device (e.g., another computer having a display,a smart phone, a tablet computer, etc.) for receiving displayinformation associated with computer 402 via any communication means,including via the Internet and cloud-based networks. In addition to themonitor 444, a computer typically comprises other peripheral outputdevices (not shown), such as speakers, printers, etc.

The computer 402 can operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, such as a remote computer(s) 448. The remotecomputer(s) 448 can be a workstation, a server computer, a router, apersonal computer, portable computer, microprocessor-based entertainmentappliance, a peer device or other common network node, and typicallycomprises many or all of the elements described relative to the computer402, although, for purposes of brevity, only a remote memory/storagedevice 450 is illustrated. The logical connections depicted comprisewired/wireless connectivity to a local area network (LAN) 452 and/orlarger networks, e.g., a wide area network (WAN) 454. Such LAN and WANnetworking environments are commonplace in offices and companies, andfacilitate enterprise-wide computer networks, such as intranets, all ofwhich can connect to a global communications network, e.g., theInternet.

When used in a LAN networking environment, the computer 402 can beconnected to the LAN 452 through a wired and/or wireless communicationnetwork interface or adapter 456. The adapter 456 can facilitate wiredor wireless communication to the LAN 452, which can also comprise awireless AP disposed thereon for communicating with the adapter 456.

When used in a WAN networking environment, the computer 402 can comprisea modem 458 or can be connected to a communications server on the WAN454 or has other means for establishing communications over the WAN 454,such as by way of the Internet. The modem 458, which can be internal orexternal and a wired or wireless device, can be connected to the systembus 408 via the input device interface 442. In a networked environment,program modules depicted relative to the computer 402 or portionsthereof, can be stored in the remote memory/storage device 450. It willbe appreciated that the network connections shown are example and othermeans of establishing a communications link between the computers can beused.

The computer 402 can be operable to communicate with any wirelessdevices or entities operatively disposed in wireless communication,e.g., a printer, scanner, desktop and/or portable computer, portabledata assistant, communications satellite, any piece of equipment orlocation associated with a wirelessly detectable tag (e.g., a kiosk,news stand, restroom), and telephone. This can comprise WirelessFidelity (Wi-Fi) and BLUETOOTH® wireless technologies. Thus, thecommunication can be a predefined structure as with a conventionalnetwork or simply an ad hoc communication between at least two devices.

Wi-Fi can allow connection to the Internet from a couch at home, a bedin a hotel room or a conference room at work, without wires. Wi-Fi is awireless technology similar to that used in a cell phone that enablessuch devices, e.g., computers, to send and receive data indoors and out;anywhere within the range of a base station. Wi-Fi networks use radiotechnologies called IEEE 802.11 (a, b, g, n, ac, ag, etc.) to providesecure, reliable, fast wireless connectivity. A Wi-Fi network can beused to connect computers to each other, to the Internet, and to wirednetworks (which can use IEEE 802.3 or Ethernet). Wi-Fi networks operatein the unlicensed 2.4 and 5 GHz radio bands for example or with productsthat contain both bands (dual band), so the networks can providereal-world performance similar to the basic 10BaseT wired Ethernetnetworks used in many offices.

Turning now to FIG. 5, an embodiment 500 of a mobile network platform510 is shown that is an example of network elements 150, 152, 154, 156,and/or VNEs 330, 332, 334, etc. For example, platform 510 can facilitatein whole or in part determining an edge latency for each of a pluralityof mobile devices according to latency test data, resulting in aplurality of edge latencies; identifying a group of mobile deviceclusters according to the plurality of edge latencies; and identifyingedge server locations for a plurality of network edge servers accordingto the group of mobile device clusters. In one or more embodiments, themobile network platform 510 can generate and receive signals transmittedand received by base stations or access points such as base station oraccess point 122. Generally, mobile network platform 510 can comprisecomponents, e.g., nodes, gateways, interfaces, servers, or disparateplatforms, that facilitate both packet-switched (PS) (e.g., internetprotocol (IP), frame relay, asynchronous transfer mode (ATM)) andcircuit-switched (CS) traffic (e.g., voice and data), as well as controlgeneration for networked wireless telecommunication. As a non-limitingexample, mobile network platform 510 can be included intelecommunications carrier networks, and can be considered carrier-sidecomponents as discussed elsewhere herein. Mobile network platform 510comprises CS gateway node(s) 512 which can interface CS traffic receivedfrom legacy networks like telephony network(s) 540 (e.g., publicswitched telephone network (PSTN), or public land mobile network (PLMN))or a signaling system #7 (SS7) network 560. CS gateway node(s) 512 canauthorize and authenticate traffic (e.g., voice) arising from suchnetworks. Additionally, CS gateway node(s) 512 can access mobility, orroaming, data generated through SS7 network 560; for instance, mobilitydata stored in a visited location register (VLR), which can reside inmemory 530. Moreover, CS gateway node(s) 512 interfaces CS-based trafficand signaling and PS gateway node(s) 518. As an example, in a 3GPP UMTSnetwork, CS gateway node(s) 512 can be realized at least in part ingateway GPRS support node(s) (GGSN). It should be appreciated thatfunctionality and specific operation of CS gateway node(s) 512, PSgateway node(s) 518, and serving node(s) 516, is provided and dictatedby radio technology(ies) utilized by mobile network platform 510 fortelecommunication over a radio access network 520 with other devices,such as a radiotelephone 575.

In addition to receiving and processing CS-switched traffic andsignaling, PS gateway node(s) 518 can authorize and authenticatePS-based data sessions with served mobile devices. Data sessions cancomprise traffic, or content(s), exchanged with networks external to themobile network platform 510, like wide area network(s) (WANs) 550,enterprise network(s) 570, and service network(s) 580, which can beembodied in local area network(s) (LANs), can also be interfaced withmobile network platform 510 through PS gateway node(s) 518. It is to benoted that WANs 550 and enterprise network(s) 570 can embody, at leastin part, a service network(s) like IP multimedia subsystem (IMS). Basedon radio technology layer(s) available in technology resource(s) orradio access network 520, PS gateway node(s) 518 can generate packetdata protocol contexts when a data session is established; other datastructures that facilitate routing of packetized data also can begenerated. To that end, in an aspect, PS gateway node(s) 518 cancomprise a tunnel interface (e.g., tunnel termination gateway (TTG) in3GPP UMTS network(s) (not shown)) which can facilitate packetizedcommunication with disparate wireless network(s), such as Wi-Finetworks.

In embodiment 500, mobile network platform 510 also comprises servingnode(s) 516 that, based upon available radio technology layer(s) withintechnology resource(s) in the radio access network 520, convey thevarious packetized flows of data streams received through PS gatewaynode(s) 518. It is to be noted that for technology resource(s) that relyprimarily on CS communication, server node(s) can deliver trafficwithout reliance on PS gateway node(s) 518; for example, server node(s)can embody at least in part a mobile switching center. As an example, ina 3GPP UMTS network, serving node(s) 516 can be embodied in serving GPRSsupport node(s) (SGSN).

For radio technologies that exploit packetized communication, server(s)514 in mobile network platform 510 can execute numerous applicationsthat can generate multiple disparate packetized data streams or flows,and manage (e.g., schedule, queue, format . . . ) such flows. Suchapplication(s) can comprise add-on features to standard services (forexample, provisioning, billing, customer support . . . ) provided bymobile network platform 510. Data streams (e.g., content(s) that arepart of a voice call or data session) can be conveyed to PS gatewaynode(s) 518 for authorization/authentication and initiation of a datasession, and to serving node(s) 516 for communication thereafter. Inaddition to application server, server(s) 514 can comprise utilityserver(s), a utility server can comprise a provisioning server, anoperations and maintenance server, a security server that can implementat least in part a certificate authority and firewalls as well as othersecurity mechanisms, and the like. In an aspect, security server(s)secure communication served through mobile network platform 510 toensure network's operation and data integrity in addition toauthorization and authentication procedures that CS gateway node(s) 512and PS gateway node(s) 518 can enact. Moreover, provisioning server(s)can provision services from external network(s) like networks operatedby a disparate service provider; for instance, WAN 550 or GlobalPositioning System (GPS) network(s) (not shown). Provisioning server(s)can also provision coverage through networks associated to mobilenetwork platform 510 (e.g., deployed and operated by the same serviceprovider), such as the distributed antennas networks shown in FIG. 1(s)that enhance wireless service coverage by providing more networkcoverage.

It is to be noted that server(s) 514 can comprise one or more processorsconfigured to confer at least in part the functionality of mobilenetwork platform 510. To that end, the one or more processor can executecode instructions stored in memory 530, for example. It is should beappreciated that server(s) 514 can comprise a content manager, whichoperates in substantially the same manner as described hereinbefore.

In example embodiment 500, memory 530 can store information related tooperation of mobile network platform 510. Other operational informationcan comprise provisioning information of mobile devices served throughmobile network platform 510, subscriber databases; applicationintelligence, pricing schemes, e.g., promotional rates, flat-rateprograms, couponing campaigns; technical specification(s) consistentwith telecommunication protocols for operation of disparate radio, orwireless, technology layers; and so forth. Memory 530 can also storeinformation from at least one of telephony network(s) 540, WAN 550, SS7network 560, or enterprise network(s) 570. In an aspect, memory 530 canbe, for example, accessed as part of a data store component or as aremotely connected memory store.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 5, and the following discussion, are intended toprovide a brief, general description of a suitable environment in whichthe various aspects of the disclosed subject matter can be implemented.While the subject matter has been described above in the general contextof computer-executable instructions of a computer program that runs on acomputer and/or computers, those skilled in the art will recognize thatthe disclosed subject matter also can be implemented in combination withother program modules. Generally, program modules comprise routines,programs, components, data structures, etc. that perform particulartasks and/or implement particular abstract data types.

Turning now to FIG. 6, an illustrative embodiment of a communicationdevice 600 is shown. The communication device 600 can serve as anillustrative embodiment of devices such as data terminals 114, mobiledevices 124, vehicle 126, display devices 144 or other client devicesfor communication via either communications network 125. For example,computing device 600 can facilitate in whole or in part determining adata center latency for each of a plurality of network edge serversaccording to latency test data, resulting in a plurality of data centerlatencies; identifying a data center location for a data centeraccording to the plurality of data center latencies, and determining anetwork topology for the communication network, the network topologyincluding the data center location and the edge server locations.

The communication device 600 can comprise a wireline and/or wirelesstransceiver 602 (herein transceiver 602), a user interface (UI) 604, apower supply 614, a location receiver 616, a motion sensor 618, anorientation sensor 620, and a controller 606 for managing operationsthereof. The transceiver 602 can support short-range or long-rangewireless access technologies such as Bluetooth®, ZigBee®, WiFi, DECT, orcellular communication technologies, just to mention a few (Bluetooth®and ZigBee® are trademarks registered by the Bluetooth® Special InterestGroup and the ZigBee® Alliance, respectively). Cellular technologies caninclude, for example, CDMA-1X, UMTS/HSDPA, GSM/GPRS, TDMA/EDGE, EV/DO,WiMAX, SDR, LTE, as well as other next generation wireless communicationtechnologies as they arise. The transceiver 602 can also be adapted tosupport circuit-switched wireline access technologies (such as PSTN),packet-switched wireline access technologies (such as TCP/IP, VoIP,etc.), and combinations thereof.

The UI 604 can include a depressible or touch-sensitive keypad 608 witha navigation mechanism such as a roller ball, a joystick, a mouse, or anavigation disk for manipulating operations of the communication device600. The keypad 608 can be an integral part of a housing assembly of thecommunication device 600 or an independent device operably coupledthereto by a tethered wireline interface (such as a USB cable) or awireless interface supporting for example Bluetooth®. The keypad 608 canrepresent a numeric keypad commonly used by phones, and/or a QWERTYkeypad with alphanumeric keys. The UI 604 can further include a display610 such as monochrome or color LCD (Liquid Crystal Display), OLED(Organic Light Emitting Diode) or other suitable display technology forconveying images to an end user of the communication device 600. In anembodiment where the display 610 is touch-sensitive, a portion or all ofthe keypad 608 can be presented by way of the display 610 withnavigation features.

The display 610 can use touch screen technology to also serve as a userinterface for detecting user input. As a touch screen display, thecommunication device 600 can be adapted to present a user interfacehaving graphical user interface (GUI) elements that can be selected by auser with a touch of a finger. The display 610 can be equipped withcapacitive, resistive or other forms of sensing technology to detect howmuch surface area of a user's finger has been placed on a portion of thetouch screen display. This sensing information can be used to controlthe manipulation of the GUI elements or other functions of the userinterface. The display 610 can be an integral part of the housingassembly of the communication device 600 or an independent devicecommunicatively coupled thereto by a tethered wireline interface (suchas a cable) or a wireless interface.

The UI 604 can also include an audio system 612 that utilizes audiotechnology for conveying low volume audio (such as audio heard inproximity of a human ear) and high volume audio (such as speakerphonefor hands free operation). The audio system 612 can further include amicrophone for receiving audible signals of an end user. The audiosystem 612 can also be used for voice recognition applications. The UI604 can further include an image sensor 613 such as a charged coupleddevice (CCD) camera for capturing still or moving images.

The power supply 614 can utilize common power management technologiessuch as replaceable and rechargeable batteries, supply regulationtechnologies, and/or charging system technologies for supplying energyto the components of the communication device 600 to facilitatelong-range or short-range portable communications. Alternatively, or incombination, the charging system can utilize external power sources suchas DC power supplied over a physical interface such as a USB port orother suitable tethering technologies.

The location receiver 616 can utilize location technology such as aglobal positioning system (GPS) receiver capable of assisted GPS foridentifying a location of the communication device 600 based on signalsgenerated by a constellation of GPS satellites, which can be used forfacilitating location services such as navigation. The motion sensor 618can utilize motion sensing technology such as an accelerometer, agyroscope, or other suitable motion sensing technology to detect motionof the communication device 600 in three-dimensional space. Theorientation sensor 620 can utilize orientation sensing technology suchas a magnetometer to detect the orientation of the communication device600 (north, south, west, and east, as well as combined orientations indegrees, minutes, or other suitable orientation metrics).

The communication device 600 can use the transceiver 602 to alsodetermine a proximity to a cellular, WiFi, Bluetooth®, or other wirelessaccess points by sensing techniques such as utilizing a received signalstrength indicator (RSSI) and/or signal time of arrival (TOA) or time offlight (TOF) measurements. The controller 606 can utilize computingtechnologies such as a microprocessor, a digital signal processor (DSP),programmable gate arrays, application specific integrated circuits,and/or a video processor with associated storage memory such as Flash,ROM, RAM, SRAM, DRAM or other storage technologies for executingcomputer instructions, controlling, and processing data supplied by theaforementioned components of the communication device 600.

Other components not shown in FIG. 6 can be used in one or moreembodiments of the subject disclosure. For instance, the communicationdevice 600 can include a slot for adding or removing an identity modulesuch as a Subscriber Identity Module (SIM) card or Universal IntegratedCircuit Card (UICC). SIM or UICC cards can be used for identifyingsubscriber services, executing programs, storing subscriber data, and soon.

The terms “first,” “second,” “third,” and so forth, as used in theclaims, unless otherwise clear by context, is for clarity only anddoesn't otherwise indicate or imply any order in time. For instance, “afirst determination,” “a second determination,” and “a thirddetermination,” does not indicate or imply that the first determinationis to be made before the second determination, or vice versa, etc.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can comprise both volatile andnonvolatile memory, by way of illustration, and not limitation, volatilememory, non-volatile memory, disk storage, and memory storage. Further,nonvolatile memory can be included in read only memory (ROM),programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable ROM (EEPROM), or flash memory. Volatile memory cancomprise random access memory (RAM), which acts as external cachememory. By way of illustration and not limitation, RAM is available inmany forms such as synchronous RAM (SRAM), dynamic RAM (DRAM),synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhancedSDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).Additionally, the disclosed memory components of systems or methodsherein are intended to comprise, without being limited to comprising,these and any other suitable types of memory.

Moreover, it will be noted that the disclosed subject matter can bepracticed with other computer system configurations, comprisingsingle-processor or multiprocessor computer systems, mini-computingdevices, mainframe computers, as well as personal computers, hand-heldcomputing devices (e.g., PDA, phone, smartphone, watch, tabletcomputers, netbook computers, etc.), microprocessor-based orprogrammable consumer or industrial electronics, and the like. Theillustrated aspects can also be practiced in distributed computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network; however, some if not allaspects of the subject disclosure can be practiced on stand-alonecomputers. In a distributed computing environment, program modules canbe located in both local and remote memory storage devices.

In one or more embodiments, information regarding use of services can begenerated including services being accessed, media consumption history,user preferences, and so forth. This information can be obtained byvarious methods including user input, detecting types of communications(e.g., video content vs. audio content), analysis of content streams,sampling, and so forth. The generating, obtaining and/or monitoring ofthis information can be responsive to an authorization provided by theuser. In one or more embodiments, an analysis of data can be subject toauthorization from user(s) associated with the data, such as an opt-in,an opt-out, acknowledgement requirements, notifications, selectiveauthorization based on types of data, and so forth.

Some of the embodiments described herein can also employ artificialintelligence (AI) to facilitate automating one or more featuresdescribed herein. The embodiments (e.g., in connection withautomatically identifying acquired cell sites that provide a maximumvalue/benefit after addition to an existing communication network) canemploy various AI-based schemes for carrying out various embodimentsthereof. Moreover, the classifier can be employed to determine a rankingor priority of each cell site of the acquired network. A classifier is afunction that maps an input attribute vector, x=(x1, x2, x3, x4, . . . ,xn), to a confidence that the input belongs to a class, that is,f(x)=confidence (class). Such classification can employ a probabilisticand/or statistical-based analysis (e.g., factoring into the analysisutilities and costs) to determine or infer an action that a user desiresto be automatically performed. A support vector machine (SVM) is anexample of a classifier that can be employed. The SVM operates byfinding a hypersurface in the space of possible inputs, which thehypersurface attempts to split the triggering criteria from thenon-triggering events. Intuitively, this makes the classificationcorrect for testing data that is near, but not identical to trainingdata. Other directed and undirected model classification approachescomprise, e.g., naïve Bayes, Bayesian networks, decision trees, neuralnetworks, fuzzy logic models, and probabilistic classification modelsproviding different patterns of independence can be employed.Classification as used herein also is inclusive of statisticalregression that is utilized to develop models of priority.

As will be readily appreciated, one or more of the embodiments canemploy classifiers that are explicitly trained (e.g., via a generictraining data) as well as implicitly trained (e.g., via observing UEbehavior, operator preferences, historical information, receivingextrinsic information). For example, SVMs can be configured via alearning or training phase within a classifier constructor and featureselection module. Thus, the classifier(s) can be used to automaticallylearn and perform a number of functions, including but not limited todetermining according to predetermined criteria which of the acquiredcell sites will benefit a maximum number of subscribers and/or which ofthe acquired cell sites will add minimum value to the existingcommunication network coverage, etc.

As used in some contexts in this application, in some embodiments, theterms “component,” “system” and the like are intended to refer to, orcomprise, a computer-related entity or an entity related to anoperational apparatus with one or more specific functionalities, whereinthe entity can be either hardware, a combination of hardware andsoftware, software, or software in execution. As an example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution,computer-executable instructions, a program, and/or a computer. By wayof illustration and not limitation, both an application running on aserver and the server can be a component. One or more components mayreside within a process and/or thread of execution and a component maybe localized on one computer and/or distributed between two or morecomputers. In addition, these components can execute from variouscomputer readable media having various data structures stored thereon.The components may communicate via local and/or remote processes such asin accordance with a signal having one or more data packets (e.g., datafrom one component interacting with another component in a local system,distributed system, and/or across a network such as the Internet withother systems via the signal). As another example, a component can be anapparatus with specific functionality provided by mechanical partsoperated by electric or electronic circuitry, which is operated by asoftware or firmware application executed by a processor, wherein theprocessor can be internal or external to the apparatus and executes atleast a part of the software or firmware application. As yet anotherexample, a component can be an apparatus that provides specificfunctionality through electronic components without mechanical parts,the electronic components can comprise a processor therein to executesoftware or firmware that confers at least in part the functionality ofthe electronic components. While various components have beenillustrated as separate components, it will be appreciated that multiplecomponents can be implemented as a single component, or a singlecomponent can be implemented as multiple components, without departingfrom example embodiments.

Further, the various embodiments can be implemented as a method,apparatus or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device or computer-readable storage/communicationsmedia. For example, computer readable storage media can include, but arenot limited to, magnetic storage devices (e.g., hard disk, floppy disk,magnetic strips), optical disks (e.g., compact disk (CD), digitalversatile disk (DVD)), smart cards, and flash memory devices (e.g.,card, stick, key drive). Of course, those skilled in the art willrecognize many modifications can be made to this configuration withoutdeparting from the scope or spirit of the various embodiments.

In addition, the words “example” and “exemplary” are used herein to meanserving as an instance or illustration. Any embodiment or designdescribed herein as “example” or “exemplary” is not necessarily to beconstrued as preferred or advantageous over other embodiments ordesigns. Rather, use of the word example or exemplary is intended topresent concepts in a concrete fashion. As used in this application, theterm “or” is intended to mean an inclusive “or” rather than an exclusive“or”. That is, unless specified otherwise or clear from context, “Xemploys A or B” is intended to mean any of the natural inclusivepermutations. That is, if X employs A; X employs B; or X employs both Aand B, then “X employs A or B” is satisfied under any of the foregoinginstances. In addition, the articles “a” and “an” as used in thisapplication and the appended claims should generally be construed tomean “one or more” unless specified otherwise or clear from context tobe directed to a singular form.

Moreover, terms such as “user equipment,” “mobile station,” “mobile,”subscriber station,” “access terminal,” “terminal,” “handset,” “mobiledevice” (and/or terms representing similar terminology) can refer to awireless device utilized by a subscriber or user of a wirelesscommunication service to receive or convey data, control, voice, video,sound, gaming or substantially any data-stream or signaling-stream. Theforegoing terms are utilized interchangeably herein and with referenceto the related drawings.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer” andthe like are employed interchangeably throughout, unless contextwarrants particular distinctions among the terms. It should beappreciated that such terms can refer to human entities or automatedcomponents supported through artificial intelligence (e.g., a capacityto make inference based, at least, on complex mathematical formalisms),which can provide simulated vision, sound recognition and so forth.

As employed herein, the term “processor” can refer to substantially anycomputing processing unit or device comprising, but not limited tocomprising, single-core processors; single-processors with softwaremultithread execution capability; multi-core processors; multi-coreprocessors with software multithread execution capability; multi-coreprocessors with hardware multithread technology; parallel platforms; andparallel platforms with distributed shared memory. Additionally, aprocessor can refer to an integrated circuit, an application specificintegrated circuit (ASIC), a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), a programmable logic controller (PLC), acomplex programmable logic device (CPLD), a discrete gate or transistorlogic, discrete hardware components or any combination thereof designedto perform the functions described herein. Processors can exploitnano-scale architectures such as, but not limited to, molecular andquantum-dot based transistors, switches and gates, in order to optimizespace usage or enhance performance of user equipment. A processor canalso be implemented as a combination of computing processing units.

As used herein, terms such as “data storage,” data storage,” “database,”and substantially any other information storage component relevant tooperation and functionality of a component, refer to “memorycomponents,” or entities embodied in a “memory” or components comprisingthe memory. It will be appreciated that the memory components orcomputer-readable storage media, described herein can be either volatilememory or nonvolatile memory or can include both volatile andnonvolatile memory.

What has been described above includes mere examples of variousembodiments. It is, of course, not possible to describe everyconceivable combination of components or methodologies for purposes ofdescribing these examples, but one of ordinary skill in the art canrecognize that many further combinations and permutations of the presentembodiments are possible. Accordingly, the embodiments disclosed and/orclaimed herein are intended to embrace all such alterations,modifications and variations that fall within the spirit and scope ofthe appended claims. Furthermore, to the extent that the term “includes”is used in either the detailed description or the claims, such term isintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

As may also be used herein, the term(s) “operably coupled to”, “coupledto”, and/or “coupling” includes direct coupling between items and/orindirect coupling between items via one or more intervening items. Suchitems and intervening items include, but are not limited to, junctions,communication paths, components, circuit elements, circuits, functionalblocks, and/or devices. As an example of indirect coupling, a signalconveyed from a first item to a second item may be modified by one ormore intervening items by modifying the form, nature or format ofinformation in a signal, while one or more elements of the informationin the signal are nevertheless conveyed in a manner than can berecognized by the second item. In a further example of indirectcoupling, an action in a first item can cause a reaction on the seconditem, as a result of actions and/or reactions in one or more interveningitems.

Although specific embodiments have been illustrated and describedherein, it should be appreciated that any arrangement which achieves thesame or similar purpose may be substituted for the embodiments describedor shown by the subject disclosure. The subject disclosure is intendedto cover any and all adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, can be used in the subject disclosure.For instance, one or more features from one or more embodiments can becombined with one or more features of one or more other embodiments. Inone or more embodiments, features that are positively recited can alsobe negatively recited and excluded from the embodiment with or withoutreplacement by another structural and/or functional feature. The stepsor functions described with respect to the embodiments of the subjectdisclosure can be performed in any order. The steps or functionsdescribed with respect to the embodiments of the subject disclosure canbe performed alone or in combination with other steps or functions ofthe subject disclosure, as well as from other embodiments or from othersteps that have not been described in the subject disclosure. Further,more than or less than all of the features described with respect to anembodiment can also be utilized.

What is claimed is:
 1. A device, comprising: a processing systemincluding a processor; and a memory that stores executable instructionsthat, when executed by the processing system, facilitate performance ofoperations comprising: receiving first latency test data from each of aplurality of mobile devices operating on a communication network;determining an edge latency for each of the plurality of mobile devicesaccording to the first latency test data, resulting in a plurality ofedge latencies; identifying a group of mobile device clusters in theplurality of mobile devices, according to the plurality of edgelatencies; identifying edge server locations for a plurality of networkedge servers according to the group of mobile device clusters; receivingsecond latency test data from each of the plurality of network edgeservers; determining a data center latency for each of the plurality ofnetwork edge servers according to the second latency test data,resulting in a plurality of data center latencies; identifying a datacenter location for a data center according to the plurality of datacenter latencies; and determining a network topology for thecommunication network, the network topology including the data centerlocation and the edge server locations.
 2. The device of claim 1,wherein the identifying the group of mobile device clusters comprisesperforming a machine learning clustering technique.
 3. The device ofclaim 1, wherein the first latency test data for a mobile device of theplurality of mobile devices includes a location of the mobile device. 4.The device of claim 1, wherein the plurality of edge latencies aredetermined from a portion of latencies in the first latency test datameeting a latency criterion.
 5. The device of claim 1, wherein theoperations further comprise enabling each of the plurality of mobiledevices to perform a latency test to obtain the first latency test data.6. The device of claim 5, wherein the latency test comprises a Pingtest, a Traceroute test, or a combination thereof.
 7. The device ofclaim 1, wherein the operations further comprise: obtaining a locationof a communication device coupled to the communication network; andestimating a latency for the communication device in accordance with thelocation of the communication device and the network topology.
 8. Thedevice of claim 7, wherein the estimated latency comprises a corenetwork latency and an internet latency for the communication device. 9.The device of claim 8, wherein the communication device has a radioaccess network (RAN) latency associated with being coupled to thecommunication network, and wherein the operations further comprisecombining the estimated latency with the RAN latency to estimate anend-to-end latency for the communication device.
 10. A machine-readablemedium comprising executable instructions that, when executed by aprocessing system including a processor, facilitate performance ofoperations comprising: enabling each of a plurality of mobile devicesoperating on a communication network to perform a latency test to obtainfirst latency test data; determining an edge latency for each of theplurality of mobile devices according to the first latency test data,resulting in a plurality of edge latencies; identifying a group ofmobile device clusters in the plurality of mobile devices, according tothe plurality of edge latencies; identifying edge server locations for aplurality of network edge servers according to the group of mobiledevice clusters; receiving second latency test data from each of theplurality of network edge servers; determining a data center latency foreach of the plurality of network edge servers according to the secondlatency test data, resulting in a plurality of data center latencies;identifying a data center location for a data center according to theplurality of data center latencies; and determining a network topologyfor the communication network, the network topology including the datacenter location and the edge server locations.
 11. The machine-readablemedium of claim 10, wherein the identifying the group of mobile deviceclusters comprises performing a machine learning clustering technique.12. The machine-readable medium of claim 10, wherein the first latencytest data for a mobile device of the plurality of mobile devicesincludes a location of the mobile device.
 13. The machine-readablemedium of claim 10, wherein the operations further comprise: obtaining alocation of a communication device coupled to the communication network;and estimating a latency for the communication device in accordance withthe location of the communication device and the network topology. 14.The machine-readable medium of claim 13, wherein the estimated latencycomprises a core network latency and an internet latency for thecommunication device.
 15. The machine-readable medium of claim 14,wherein the communication device has a radio access network (RAN)latency associated with being coupled to the communication network, andwherein the operations further comprise combining the estimated latencywith the RAN latency to estimate an end-to-end latency for thecommunication device.
 16. A method, comprising: receiving, by aprocessing system including a processor, first latency test data fromeach of a plurality of mobile devices operating on a communicationnetwork; determining, by the processing system, an edge latency for eachof the plurality of mobile devices according to the first latency testdata, resulting in a plurality of edge latencies; identifying, by theprocessing system, a group of mobile device clusters in the plurality ofmobile devices according to the plurality of edge latencies byperforming a machine learning clustering technique; identifying, by theprocessing system, edge server locations for a plurality of network edgeservers according to the group of mobile device clusters; receiving, bythe processing system, second latency test data from each of theplurality of network edge servers; determining, by the processingsystem, a data center latency for each of the plurality of network edgeservers according to the second latency test data, resulting in aplurality of data center latencies; identifying, by the processingsystem, a data center location for a data center according to theplurality of data center latencies; and determining, by the processingsystem, a network topology for the communication network, the networktopology including the data center location and the edge serverlocations.
 17. The method of claim 16, wherein the plurality of edgelatencies are determined from a portion of latencies in the firstlatency test data meeting a latency criterion.
 18. The method of claim16, further comprising: obtaining a location of a communication devicecoupled to the communication network; and estimating a latency for thecommunication device in accordance with the location of thecommunication device and the network topology.
 19. The method of claim18, wherein the estimated latency comprises a core network latency andan internet latency for the communication device.
 20. The method ofclaim 19, wherein the communication device has a radio access network(RAN) latency associated with being coupled to the communicationnetwork, and further comprising combining, by the processing system, theestimated latency with the RAN latency to estimate an end-to-end latencyfor the communication device.